AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Biological Evolution

Showing 1 to 10 of 154 articles

Clear Filters

The changing landscape of text mining: a review of approaches for ecology and evolution.

Proceedings. Biological sciences
In ecology and evolutionary biology, the synthesis and modelling of data from published literature are commonly used to generate insights and test theories across systems. However, the tasks of searching, screening, and extracting data from literatur...

Merging sociality and robotics through an evolutionary perspective.

Science robotics
Robotics, using social mechanisms like hormonal modulation, may accelerate our understanding of core sociality principles.

Inferring the locomotor ecology of two of the oldest fossil squirrels: influence of operationalization, trait, body size and machine learning method.

Proceedings. Biological sciences
Correlations between morphology and lifestyle of extant taxa are useful for predicting lifestyles of extinct relatives. Here, we infer the locomotor behaviour of from the middle Oligocene and from the lower Miocene of France using their femoral mor...

Adapting to time: Why nature may have evolved a diverse set of neurons.

PLoS computational biology
Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explor...

Neuroevolution insights into biological neural computation.

Science (New York, N.Y.)
This article reviews existing work and future opportunities in neuroevolution, an area of machine learning in which evolutionary optimization methods such as genetic algorithms are used to construct neural networks to achieve desired behavior. The ar...

Neural networks through the lens of evolutionary dynamics.

Bio Systems
This article revisits Artificial Neural Networks (NNs) through the lens of Evolutionary Dynamics. The two most important features of NNs are shown to reflect the two most general processes of Evolutionary Dynamics. This overlap may serve as a new and...

Evolutionary multi-agent reinforcement learning in group social dilemmas.

Chaos (Woodbury, N.Y.)
Reinforcement learning (RL) is a powerful machine learning technique that has been successfully applied to a wide variety of problems. However, it can be unpredictable and produce suboptimal results in complicated learning environments. This is espec...

Colonial bacterial memetic algorithm and its application on a darts playing robot.

Scientific reports
In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. CBMA extends the Bacterial Memetic Algorithm by integrating Cultural Algorithms and co-evolutionary dy...

A neural network model for the evolution of reconstructive social learning.

Scientific reports
Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transm...

Exploring the evolutionary adaptations of the unique seahorse tail's muscle architecture through modelling and robotic prototyping.

Journal of the Royal Society, Interface
Seahorses possess a unique tail muscle architecture that enables efficient grasping and anchoring onto objects. This prehensile ability is crucial for their survival, as it allows them to resist currents, cling to mates during reproduction and remain...